The Near Future of AI [Entire Talk] - Andrew Ng (AI Fund)

The first paragraph introduces Andrew, a prominent figure in the field of AI, and provides a detailed account of his educational and professional background. Born in the UK to parents from Hong Kong, Andrew was raised in Hong Kong and Singapore. He pursued three bachelor's degrees in computer science, statistics, and economics from Carnegie Mellon, followed by a master's degree in electrical engineering and computer science from MIT. He later obtained a PhD in computer science from Berkeley, with a focus on artificial intelligence and reinforcement learning. Andrew is recognized as a thought leader in AI and has held significant positions such as co-founder and head of Google Brain and former Chief Scientist at Baidu. He is also a beloved professor at Stanford and co-founder and chairman of Coursera, an online education platform. His work in AI education has reached over 7 million people, and he was listed as one of the world's 100 most influential people by Time magazine in 2013. Andrew is currently the managing director and partner at the AI Fund, a startup studio focused on building new AI companies from the ground up.

In this paragraph, Andrew discusses the revolutionary impact of prompting in the development of AI applications. He explains that unlike traditional supervised learning, which can take months or even years to build and deploy an AI system, prompting has significantly reduced the timeline to mere hours or days. This has been made possible by large language models, which have lowered the barrier to building AI applications. Andrew also highlights the potential of these models as a developer tool, enabling the creation of more AI applications and transforming the startup landscape. He shares his excitement about the rapid development times and the shift towards building multiple prototypes to see what sticks with users, emphasizing the importance of responsible AI practices in this process.

Andrew delves into the opportunities presented by AI technologies, emphasizing their general-purpose nature similar to electricity. He discusses the major trends in AI and the growth of supervised learning over the past decade, which has been highly valuable for companies like Google. He also highlights the potential of generative AI, which, although currently smaller in revenue, is growing rapidly and could double in value within three years. Andrew illustrates the opportunities in AI by discussing the AI stack, including hardware, cloud infrastructure, developer tooling, and the application layer. He sees the most significant opportunities in the application layer, where the competition is less intense, and encourages entrepreneurs to explore concrete use cases for AI in various fields.

Andrew shares insights into building AI startups and the role of AI across different industries. He discusses the importance of identifying and pursuing diverse opportunities in AI, which led him to start the AI Fund, a venture studio that collaborates with entrepreneurs to launch companies. Andrew explains that AI technology allows for the pursuit of projects that were not possible a few years ago, and he emphasizes the potential of AI in incumbent companies due to their distribution advantage. He also highlights the importance of responsible AI and the need to kill projects that may be financially sound but ethically questionable. Andrew's team focuses on projects that move humanity forward and have a positive impact on society.

Andrew offers advice to students interested in pursuing a career in AI. He emphasizes the importance of taking classes to gain foundational skills in AI technology and entrepreneurship. He suggests that coursework is an efficient way to learn, as professors organize material in a way that is easy to understand. Andrew also encourages students to apply their AI expertise to different disciplines to find exciting applications. He advocates for learning how to code, as it increases the ability to accomplish tasks and is beneficial in the era of data accessibility. Andrew also stresses the importance of responsible AI and moving projects forward that have a positive impact on humanity.

In this paragraph, Andrew addresses concerns about the existential threat of AI to humanity, expressing his disagreement with the notion. He compares AI to other powerful entities like corporations and nation-states that humanity has experience controlling. Andrew sees AI as similar to airplanes, which, despite initial risks, became safe through regulation and learning from past experiences. He criticizes the narrative of AI extinction as harmful, especially in deterring students from pursuing careers in AI due to fears of contributing to potential human extinction. Andrew also discusses the next big shifts in AI, predicting advancements in visual AI and the rise of edge AI, where applications run on local devices like laptops and cell phones. He also touches on the importance of addressing security concerns related to AI models, such as prompt injections and data leakage.

Andrew discusses the global development of AI capabilities and the potential for local opportunities in different regions. He notes that while deep tech talent is concentrated in the San Francisco Bay Area, the application layer skills are developing quickly worldwide. Andrew sees potential in businesses that play locally, leveraging the strengths of their geography. He also addresses the challenges of accessing certain AI resources from specific regions, such as Hong Kong. Furthermore, Andrew shares his thoughts on the future dependence on AI, suggesting that our reliance on technology will continue to grow. He discusses the concept of technological singularity but expresses uncertainty about its definition and occurrence. Andrew also explores AI-driven healthcare applications, emphasizing the opportunities in diagnostics, treatment, and healthcare operations, while also acknowledging the regulatory and revenue model challenges.

Andrew shares the process his team at the AI Fund uses for generating ideas for AI applications. He highlights the value of working with subject matter experts who have deep domain knowledge and have thought extensively about specific issues. These experts often have ideas they want to validate or build, and collaborating with them can lead to exciting AI projects. Andrew emphasizes the importance of combining AI expertise with domain-specific knowledge to identify and develop innovative AI applications that can have a significant impact on various industries.